01 - exploración.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Hernandez484/01.01-PROYECTO-KAGGLE/blob/main/01_exploraci%C3%B3n.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<img 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\">"
      ],
      "metadata": {
        "id": "75UCTyLKGFdl"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# <font color='056938'> **01.01 - PROYECTO KAGGLE - </font> <font color='8EC044'> Entrega 1** </font>"
      ],
      "metadata": {
        "id": "8k-QjmaTD0jt"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## <font color='157699'> **Paso 1:** </font>"
      ],
      "metadata": {
        "id": "rfqLEMKiNMiC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!wget --no-cache -O init.py -q https://raw.githubusercontent.com/rramosp/ai4eng.v1/main/content/init.py\n",
        "import init; init.init(force_download=False); init.get_weblink()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "cY4OuKdwrD_c",
        "outputId": "71d3e2fb-dc50-4fb6-ae31-3474cb79fa47"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "<meta name=\"google-signin-client_id\"\n",
              "      content=\"461673936472-kdjosv61up3ac1ajeuq6qqu72upilmls.apps.googleusercontent.com\"/>\n",
              "<script src=\"https://apis.google.com/js/client:platform.js?onload=google_button_start\"></script>\n",
              "    "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "replicating local resources\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<h3>See <a href='https://m5knaekxo6.execute-api.us-west-2.amazonaws.com/dev-v0001/rlxmooc/web/login' target='_blank'>my courses and progress</a></h2>"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## <font color='157699'> **Paso 2: Descargar datos directamente desde Kaggle** </font>\n",
        "\n",
        "- Se creo un archivo kaggle.jsoncon con mi token de autenticación (en kaggle $\\to$ Hago clic en el icono de usuario en la parte superior derecha $\\to$\n",
        "ajustes $\\to$ API crea un nuevo token);\n",
        "\n",
        "- Subirlo a este espacio de trabajo del cuaderno;\n",
        "\n",
        "- Y ejecutar la siguiente celda."
      ],
      "metadata": {
        "id": "wCY2PW3DK9Bx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.environ['KAGGLE_CONFIG_DIR'] = '.'\n",
        "!chmod 600 ./kaggle.json\n",
        "!kaggle competitions download -c udea-ai4eng-20242"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "dZH8adx8MfpR",
        "outputId": "48ca14de-ec3d-45c8-c64b-f45d0ff6f2f6"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading udea-ai4eng-20242.zip to /content\n",
            " 40% 8.00M/20.1M [00:00<00:00, 83.6MB/s]\n",
            "100% 20.1M/20.1M [00:00<00:00, 131MB/s] \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## <font color='157699'> **Paso 3: Descomprimir e inspeccionar datos** </font>\n",
        "\n",
        "Se descomprime el fichero."
      ],
      "metadata": {
        "id": "LoXrcRMxNWP9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip udea*.zip > /dev/null"
      ],
      "metadata": {
        "id": "Gad7Ds8fN3mR"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!wc *.csv"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fchKDjNuO-dx",
        "outputId": "63940327-0834-4c25-9e41-67b59afe1388"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   296787    296787   4716673 submission_example.csv\n",
            "   296787   4565553  50135751 test.csv\n",
            "   692501  10666231 118025055 train.csv\n",
            "  1286075  15528571 172877479 total\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## <font color='157699'> **Paso 4: Se carga `train.csv` con la librería `Pandas`** </font>"
      ],
      "metadata": {
        "id": "LVJBDWy2N7Vh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "\n",
        "z = pd.read_csv(\"train.csv\")\n",
        "print (\"shape of loaded dataframe\", z.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Sqzqg0izWeqJ",
        "outputId": "97d89aca-6e34-4166-b355-cf3df1921cf8"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "shape of loaded dataframe (692500, 12)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "XEdSYvj3WuGL",
        "outputId": "6c89dde6-21bc-4af1-f805-435d8c5e1140"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       ID  PERIODO         ESTU_PRGM_ACADEMICO ESTU_PRGM_DEPARTAMENTO  \\\n",
              "0  904256    20212                  ENFERMERIA                 BOGOTÁ   \n",
              "1  645256    20212                     DERECHO              ATLANTICO   \n",
              "2  308367    20203       MERCADEO Y PUBLICIDAD                 BOGOTÁ   \n",
              "3  470353    20195  ADMINISTRACION DE EMPRESAS              SANTANDER   \n",
              "4  989032    20212                  PSICOLOGIA              ANTIOQUIA   \n",
              "\n",
              "             ESTU_VALORMATRICULAUNIVERSIDAD ESTU_HORASSEMANATRABAJA  \\\n",
              "0  Entre 5.5 millones y menos de 7 millones       Menos de 10 horas   \n",
              "1  Entre 2.5 millones y menos de 4 millones                       0   \n",
              "2  Entre 2.5 millones y menos de 4 millones         Más de 30 horas   \n",
              "3  Entre 4 millones y menos de 5.5 millones                       0   \n",
              "4  Entre 2.5 millones y menos de 4 millones     Entre 21 y 30 horas   \n",
              "\n",
              "  FAMI_ESTRATOVIVIENDA FAMI_TIENEINTERNET                 FAMI_EDUCACIONPADRE  \\\n",
              "0            Estrato 3                 Si    Técnica o tecnológica incompleta   \n",
              "1            Estrato 3                 No      Técnica o tecnológica completa   \n",
              "2            Estrato 3                 Si  Secundaria (Bachillerato) completa   \n",
              "3            Estrato 4                 Si                             No sabe   \n",
              "4            Estrato 3                 Si                   Primaria completa   \n",
              "\n",
              "                  FAMI_EDUCACIONMADRE ESTU_PAGOMATRICULAPROPIO  \\\n",
              "0                           Postgrado                       No   \n",
              "1    Técnica o tecnológica incompleta                       No   \n",
              "2  Secundaria (Bachillerato) completa                       No   \n",
              "3  Secundaria (Bachillerato) completa                       No   \n",
              "4                   Primaria completa                       No   \n",
              "\n",
              "  RENDIMIENTO_GLOBAL  \n",
              "0         medio-alto  \n",
              "1               bajo  \n",
              "2               bajo  \n",
              "3               alto  \n",
              "4         medio-bajo  "
            ],
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              "\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>PERIODO</th>\n",
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              "      <td>904256</td>\n",
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              "      <td>Entre 5.5 millones y menos de 7 millones</td>\n",
              "      <td>Menos de 10 horas</td>\n",
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              "      <td>0</td>\n",
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              "      <td>No</td>\n",
              "      <td>Técnica o tecnológica completa</td>\n",
              "      <td>Técnica o tecnológica incompleta</td>\n",
              "      <td>No</td>\n",
              "      <td>bajo</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>308367</td>\n",
              "      <td>20203</td>\n",
              "      <td>MERCADEO Y PUBLICIDAD</td>\n",
              "      <td>BOGOTÁ</td>\n",
              "      <td>Entre 2.5 millones y menos de 4 millones</td>\n",
              "      <td>Más de 30 horas</td>\n",
              "      <td>Estrato 3</td>\n",
              "      <td>Si</td>\n",
              "      <td>Secundaria (Bachillerato) completa</td>\n",
              "      <td>Secundaria (Bachillerato) completa</td>\n",
              "      <td>No</td>\n",
              "      <td>bajo</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>470353</td>\n",
              "      <td>20195</td>\n",
              "      <td>ADMINISTRACION DE EMPRESAS</td>\n",
              "      <td>SANTANDER</td>\n",
              "      <td>Entre 4 millones y menos de 5.5 millones</td>\n",
              "      <td>0</td>\n",
              "      <td>Estrato 4</td>\n",
              "      <td>Si</td>\n",
              "      <td>No sabe</td>\n",
              "      <td>Secundaria (Bachillerato) completa</td>\n",
              "      <td>No</td>\n",
              "      <td>alto</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>989032</td>\n",
              "      <td>20212</td>\n",
              "      <td>PSICOLOGIA</td>\n",
              "      <td>ANTIOQUIA</td>\n",
              "      <td>Entre 2.5 millones y menos de 4 millones</td>\n",
              "      <td>Entre 21 y 30 horas</td>\n",
              "      <td>Estrato 3</td>\n",
              "      <td>Si</td>\n",
              "      <td>Primaria completa</td>\n",
              "      <td>Primaria completa</td>\n",
              "      <td>No</td>\n",
              "      <td>medio-bajo</td>\n",
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              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f063a403-c345-4107-9fb9-aeeeda195a69 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f063a403-c345-4107-9fb9-aeeeda195a69');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
              "\n",
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              "      --bg-color: #E8F0FE;\n",
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              "      --hover-bg-color: #E2EBFA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
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              "  .colab-df-quickchart-complete:disabled,\n",
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              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-32d631e6-4b8e-4449-92a2-674ca71d1fa3 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "z"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## <font color='157699'> **Paso 5: Explaración de datos usando `train.CSV`** </font>\n",
        "\n",
        "- Se tiene que predecir la etiqueta `RENDIMIENTO_GLOBAL` usando el resto de los atributos.\n",
        "\n",
        "- Se usaran los siguientes atributos para el modelo:\n",
        "\n",
        "   - **PERIODO.**\n",
        "\n",
        "   - **FAMI_ESTRATOVIVIENDA.**\n",
        "\n",
        "   - **FAMI_EDUCACIONPADRE.**\n",
        "   \n",
        "   - **FAMI_EDUCACIONMADRE.**\n",
        "   \n",
        "   - **ESTU_PAGOMATRICULAPROPIO.**\n",
        "\n",
        "   - **ESTU_HORASSEMANATRABAJA.**\n",
        "\n",
        "   - **ESTU_VALORMATRICULAUNIVERSIDAD.**"
      ],
      "metadata": {
        "id": "HzJnGsWcY7zI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "z = z[['PERIODO', 'FAMI_ESTRATOVIVIENDA', 'FAMI_EDUCACIONPADRE', 'FAMI_EDUCACIONMADRE', 'ESTU_PAGOMATRICULAPROPIO', 'ESTU_HORASSEMANATRABAJA', 'ESTU_VALORMATRICULAUNIVERSIDAD', 'RENDIMIENTO_GLOBAL']]\n",
        "z.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "krsBEPWoj_M4",
        "outputId": "9a3159c3-f16d-46d1-e0cc-1d6a7675a1b0"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   PERIODO FAMI_ESTRATOVIVIENDA                 FAMI_EDUCACIONPADRE  \\\n",
              "0    20212            Estrato 3    Técnica o tecnológica incompleta   \n",
              "1    20212            Estrato 3      Técnica o tecnológica completa   \n",
              "2    20203            Estrato 3  Secundaria (Bachillerato) completa   \n",
              "3    20195            Estrato 4                             No sabe   \n",
              "4    20212            Estrato 3                   Primaria completa   \n",
              "\n",
              "                  FAMI_EDUCACIONMADRE ESTU_PAGOMATRICULAPROPIO  \\\n",
              "0                           Postgrado                       No   \n",
              "1    Técnica o tecnológica incompleta                       No   \n",
              "2  Secundaria (Bachillerato) completa                       No   \n",
              "3  Secundaria (Bachillerato) completa                       No   \n",
              "4                   Primaria completa                       No   \n",
              "\n",
              "  ESTU_HORASSEMANATRABAJA            ESTU_VALORMATRICULAUNIVERSIDAD  \\\n",
              "0       Menos de 10 horas  Entre 5.5 millones y menos de 7 millones   \n",
              "1                       0  Entre 2.5 millones y menos de 4 millones   \n",
              "2         Más de 30 horas  Entre 2.5 millones y menos de 4 millones   \n",
              "3                       0  Entre 4 millones y menos de 5.5 millones   \n",
              "4     Entre 21 y 30 horas  Entre 2.5 millones y menos de 4 millones   \n",
              "\n",
              "  RENDIMIENTO_GLOBAL  \n",
              "0         medio-alto  \n",
              "1               bajo  \n",
              "2               bajo  \n",
              "3               alto  \n",
              "4         medio-bajo  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-290da544-231b-4057-bdbb-08e3a00e726f\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PERIODO</th>\n",
              "      <th>FAMI_ESTRATOVIVIENDA</th>\n",
              "      <th>FAMI_EDUCACIONPADRE</th>\n",
              "      <th>FAMI_EDUCACIONMADRE</th>\n",
              "      <th>ESTU_PAGOMATRICULAPROPIO</th>\n",
              "      <th>ESTU_HORASSEMANATRABAJA</th>\n",
              "      <th>ESTU_VALORMATRICULAUNIVERSIDAD</th>\n",
              "      <th>RENDIMIENTO_GLOBAL</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20212</td>\n",
              "      <td>Estrato 3</td>\n",
              "      <td>Técnica o tecnológica incompleta</td>\n",
              "      <td>Postgrado</td>\n",
              "      <td>No</td>\n",
              "      <td>Menos de 10 horas</td>\n",
              "      <td>Entre 5.5 millones y menos de 7 millones</td>\n",
              "      <td>medio-alto</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20212</td>\n",
              "      <td>Estrato 3</td>\n",
              "      <td>Técnica o tecnológica completa</td>\n",
              "      <td>Técnica o tecnológica incompleta</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Entre 2.5 millones y menos de 4 millones</td>\n",
              "      <td>bajo</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20203</td>\n",
              "      <td>Estrato 3</td>\n",
              "      <td>Secundaria (Bachillerato) completa</td>\n",
              "      <td>Secundaria (Bachillerato) completa</td>\n",
              "      <td>No</td>\n",
              "      <td>Más de 30 horas</td>\n",
              "      <td>Entre 2.5 millones y menos de 4 millones</td>\n",
              "      <td>bajo</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20195</td>\n",
              "      <td>Estrato 4</td>\n",
              "      <td>No sabe</td>\n",
              "      <td>Secundaria (Bachillerato) completa</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Entre 4 millones y menos de 5.5 millones</td>\n",
              "      <td>alto</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20212</td>\n",
              "      <td>Estrato 3</td>\n",
              "      <td>Primaria completa</td>\n",
              "      <td>Primaria completa</td>\n",
              "      <td>No</td>\n",
              "      <td>Entre 21 y 30 horas</td>\n",
              "      <td>Entre 2.5 millones y menos de 4 millones</td>\n",
              "      <td>medio-bajo</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-290da544-231b-4057-bdbb-08e3a00e726f')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-290da544-231b-4057-bdbb-08e3a00e726f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-290da544-231b-4057-bdbb-08e3a00e726f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-00459198-6c76-4618-a038-f10deda4b1b0\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-00459198-6c76-4618-a038-f10deda4b1b0')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-00459198-6c76-4618-a038-f10deda4b1b0 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "z"
            }
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "AZHDhqJ5TiWv",
        "outputId": "d41e5cdf-e10a-4755-cc3a-88089a434053"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             PERIODO\n",
              "count  692500.000000\n",
              "mean    20198.366679\n",
              "std        10.535037\n",
              "min     20183.000000\n",
              "25%     20195.000000\n",
              "50%     20195.000000\n",
              "75%     20203.000000\n",
              "max     20213.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8a882669-6437-430c-8f1c-1683c2c4f04d\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PERIODO</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>692500.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>20198.366679</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>10.535037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>20183.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>20195.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>20195.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>20203.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>20213.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8a882669-6437-430c-8f1c-1683c2c4f04d')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-8a882669-6437-430c-8f1c-1683c2c4f04d button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-8a882669-6437-430c-8f1c-1683c2c4f04d');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-5dc47151-7062-407b-b5fb-f88430c7aea5\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5dc47151-7062-407b-b5fb-f88430c7aea5')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-5dc47151-7062-407b-b5fb-f88430c7aea5 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"z\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"PERIODO\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 238818.80335083016,\n        \"min\": 10.53503675454003,\n        \"max\": 692500.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          692500.0,\n          20198.36667870036,\n          20203.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Después de seleccionar los datos, se procede a inspeccionar la distribución del contenido de los atributos del **Modelo 1** y de la etiqueta `RENDIMIENTO_GLOBAL`:"
      ],
      "metadata": {
        "id": "NqLM5qLMe5aa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "z.FAMI_ESTRATOVIVIENDA.value_counts().plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 528
        },
        "id": "596kpxX6aRbr",
        "outputId": "70ad8232-adf6-4368-a7af-07765bf851fd"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='FAMI_ESTRATOVIVIENDA'>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z.FAMI_EDUCACIONPADRE.value_counts().plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 711
        },
        "id": "kqFBxaXxdFhb",
        "outputId": "6a373aac-0ed2-41e6-8fe2-aa7173f1626e"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='FAMI_EDUCACIONPADRE'>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z.FAMI_EDUCACIONMADRE.value_counts().plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 711
        },
        "id": "yUNRaTuSdGsm",
        "outputId": "ca281eb5-788c-4c3b-feab-2bce5c53dd19"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='FAMI_EDUCACIONMADRE'>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z.ESTU_PAGOMATRICULAPROPIO.value_counts().plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 476
        },
        "id": "eR1PPwwwdHPO",
        "outputId": "377183be-0e99-4146-a2b6-a54479babc0b"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='ESTU_PAGOMATRICULAPROPIO'>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z.ESTU_HORASSEMANATRABAJA.value_counts().plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 589
        },
        "id": "7YxzGHaDdHuF",
        "outputId": "c7974ce1-0e84-46b4-b1bd-8f54428dfd42"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='ESTU_HORASSEMANATRABAJA'>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z.ESTU_VALORMATRICULAUNIVERSIDAD.value_counts().plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 739
        },
        "id": "UGnauEcSdII8",
        "outputId": "5c8641e6-d7a9-4843-e1c7-c8c898597ccc"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='ESTU_VALORMATRICULAUNIVERSIDAD'>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z.RENDIMIENTO_GLOBAL.value_counts().plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 531
        },
        "id": "tRlkidcOgRoo",
        "outputId": "4fa015f0-ef99-4f24-e7f4-319448ad46bb"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='RENDIMIENTO_GLOBAL'>"
            ]
          },
          "metadata": {},
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## <font color='157699'> **Paso 6: Inspeccionar visualmente si los atributos del Modelo 1, tienen un comportamiento distintivo con respecto a lo que se quiere predecir** </font>"
      ],
      "metadata": {
        "id": "lNQNH_R7eHwC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from rlxutils import subplots\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "c = sorted(z.FAMI_ESTRATOVIVIENDA.value_counts().index)\n",
        "for ax,ci in subplots(c, n_cols=4, usizex=4):\n",
        "    zc = z[z.FAMI_ESTRATOVIVIENDA==ci]\n",
        "    zc.RENDIMIENTO_GLOBAL.value_counts()[['bajo', 'medio-bajo', 'medio-alto', 'alto']].plot(kind='bar')\n",
        "    plt.title(ci)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "collapsed": true,
        "id": "y8PgJL1_dItC",
        "outputId": "7fdbeeb0-86a7-41f3-9a78-637c62679513"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x600 with 7 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from rlxutils import subplots\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "c = sorted(z.FAMI_EDUCACIONPADRE.value_counts().index)\n",
        "for ax,ci in subplots(c, n_cols=4, usizex=4):\n",
        "    zc = z[z.FAMI_EDUCACIONPADRE==ci]\n",
        "    zc.RENDIMIENTO_GLOBAL.value_counts()[['bajo', 'medio-bajo', 'medio-alto', 'alto']].plot(kind='bar')\n",
        "    plt.title(ci)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 665
        },
        "id": "-sPJ2XUHh9ms",
        "outputId": "f6c12c7c-78da-4cbb-8c98-ac5e36f461cd"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x900 with 12 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from rlxutils import subplots\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "c = sorted(z.FAMI_EDUCACIONMADRE.value_counts().index)\n",
        "for ax,ci in subplots(c, n_cols=4, usizex=4):\n",
        "    zc = z[z.FAMI_EDUCACIONMADRE==ci]\n",
        "    zc.RENDIMIENTO_GLOBAL.value_counts()[['bajo', 'medio-bajo', 'medio-alto', 'alto']].plot(kind='bar')\n",
        "    plt.title(ci)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 665
        },
        "id": "HQY_7erSh9U9",
        "outputId": "6f6dfba4-a48a-451a-fbf5-a7c4a17c76c3"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x900 with 12 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from rlxutils import subplots\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "c = sorted(z.ESTU_PAGOMATRICULAPROPIO.value_counts().index)\n",
        "for ax,ci in subplots(c, n_cols=4, usizex=4):\n",
        "    zc = z[z.ESTU_PAGOMATRICULAPROPIO==ci]\n",
        "    zc.RENDIMIENTO_GLOBAL.value_counts()[['bajo', 'medio-bajo', 'medio-alto', 'alto']].plot(kind='bar')\n",
        "    plt.title(ci)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 307
        },
        "id": "AQeMxi8oh9C-",
        "outputId": "cc0652da-fb68-402c-a730-56e613a60d73"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x300 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from rlxutils import subplots\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "c = sorted(z.ESTU_HORASSEMANATRABAJA.value_counts().index)\n",
        "for ax,ci in subplots(c, n_cols=4, usizex=4):\n",
        "    zc = z[z.ESTU_HORASSEMANATRABAJA==ci]\n",
        "    zc.RENDIMIENTO_GLOBAL.value_counts()[['bajo', 'medio-bajo', 'medio-alto', 'alto']].plot(kind='bar')\n",
        "    plt.title(ci)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "id": "_ip8xzdNh8vs",
        "outputId": "a5785669-9410-45a7-c7a8-2a8e5b25aeab"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x600 with 5 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from rlxutils import subplots\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "c = sorted(z.ESTU_VALORMATRICULAUNIVERSIDAD.value_counts().index)\n",
        "for ax,ci in subplots(c, n_cols=4, usizex=4):\n",
        "    zc = z[z.ESTU_VALORMATRICULAUNIVERSIDAD==ci]\n",
        "    zc.RENDIMIENTO_GLOBAL.value_counts()[['bajo', 'medio-bajo', 'medio-alto', 'alto']].plot(kind='bar')\n",
        "    plt.title(ci)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "Cl12yKSAh8On",
        "outputId": "f020f79e-a603-4bb9-f69c-e1381f3beba2"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x600 with 8 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    }
  ]
}